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| import streamlit as st | |
| from transformers import pipeline | |
| # Initialize the image captioning pipeline | |
| captioner = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base") | |
| # Streamlit app title | |
| st.title("Image to Text Captioning") | |
| # Input for image URL | |
| image_url = st.text_input("Enter the URL of the image:") | |
| # If an image URL is provided | |
| if image_url: | |
| try: | |
| # Display the image | |
| st.image(image_url, caption="Provided Image", use_column_width=True) | |
| # Generate the caption | |
| caption = captioner(image_url) | |
| # Display the caption | |
| st.write("**Generated Caption:**") | |
| st.write(caption[0]['generated_text']) | |
| except Exception as e: | |
| st.error(f"An error occurred: {e}") | |
| # To run this app, save this code to a file (e.g., `app.py`) and run `streamlit run app.py` in your terminal. | |